The terms “data analyst” and “data scientist” are often used interchangeably, as both jobs are critical when it comes to analyzing corporate data in meaningful ways. However, the jobs themselves are actually quite distinct. Each comes with different responsibilities and each job title requires unique qualifications. So just what are the differences between the two?

What is a Data Analyst?

Data analysts are tasked with collecting, manipulating, and of course, analyzing data. They take that data and prepare reports which detail their results. Analysts are also responsible for guarding and protecting the data they work with. Data analysts almost always hold bachelor’s degrees, and many have master’s degrees in business intelligence specializations. If they continue their education, many data analysts move on to become data scientists.

Data Analysts

According to Glassdoor, the median salary for data analysts in the United States is $60,000. Salaries range from $43,000 on the low end to $86,000 on the high end.

The skills and qualifications of data analysts typically include:

A solid understanding of data stuctures

A solid understanding of BI concepts

Experience with SQL

Experience with Hadoop platforms

Familiarity with ETL tools

Schema design

Data architecture

Data Scientists

Data scientists hold master of science and PhDs in subjects like math, statistics, operations research, or machine learning. They also go a step beyond technical expertise, and many also hold MBAs. Why? Strong business acumen is required in order to effectively address business problems. Data scientists have to be able to communicate their findings with IT leaders and other non-technical business leaders, as their work influences the way an organization makes decisions and approaches problems.

According to Glassdoor, the median salary for data scientists in the United States is $115,000, with salaries ranging from $80,000 on the low end to $146,000 on the high end. The level of education factors into higher compensation levels.

The skills and qualifications of data scientists typically include:

Familiarity with SQL

Expertise in analytics functions (median, rank, over, etc.)

Predictive modeling and analytics skills

Math, statistics, and correlation expertise

Data mining

Excel, SAS, MATLAB experience

Extensive experience working with extremely large data sets and visualization

The individual needs of the organization often dictate the exact skills required of their data scientists. Industry-specific expertise is very important, and most data scientists typically focus on one specialty throughout their careers.

If you are a data analyst or a data scientist looking for new opportunities, contact OnBoard Recruitment Advisers today. We specialize in analytics and data-related positions in a variety of fields, and we can help connect you with the right opportunity to take your career to the next level.

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About OnBoard

OnBoard Recruitment specializes in analytics, insights and data-related positions found within Marketing, Sales, Operations, Finance and IT organizations of companies. With a nationwide reach, we have experience recruiting experienced analysts, managers and senior executives. We have also helped clients hire talent directly from graduate programs.

Hiring profiles for our searches typically call for a degree in a quantitative area of study, such as mathematics, statistics or economics; experience with statistical packages such as SAS, SPSS or R; expert knowledge of Excel; and the ability to interpret and present data visually. Communication skills are also important to tell the story behind the data. Executive level positions require strategic thinking to advocate actionable insights for business decisions.

Titles may include:

Advanced Analytics

Data Scientist

Statistical Analyst

Customer Insights

Digital Marketing/ CRM

Operations Analyst

Pricing Analyst

Research Analyst

Big Data

Informatics Analyst

Data Management

Please contact us if your company is expanding or upgrading capabilities in these areas. We can offer insights and best practices for growing and retaining analytic talent.